1. Field of the Invention
This invention relates generally to camera-based detection of a clear driving path for a vehicle and, more particularly, to a method and system for detecting a clear driving path for a vehicle which uses a first classifier trained by training samples, adds a second classifier trained by reliable test samples, and uses both classifiers to reach a joint decision about a clear driving path in the road ahead.
2. Discussion of the Related Art
Many modern vehicles include sophisticated electronic systems designed to enhance the safety, comfort, and convenience of the occupants. Among these systems, driving assistance systems have become increasingly popular. Driving assistance systems require information about what lies ahead of the vehicle in order to determine if any sort of driver warning should be issued or evasive action should be taken.
Various technologies can be used for road detection by driving assistance systems to determine if the path ahead of the vehicle is clear or obstructed. Camera-based systems are widely used for clear path detection, as they have proven to be reliable and low in cost. In camera-based systems, an onboard camera provides images of the path ahead of the vehicle, and the images are processed through various algorithms to determine if the path ahead is clear or not. A common processing method is to use trained classifiers to make a clear path determination.
Trained classifiers are a class of machine learning techniques in which a set of training samples, in this case image regions of clear path roadways, is used to train a model to classify image regions of roadways which have yet to be encountered. A fundamental limitation of trained classifiers is that only a finite number of training samples can be employed, and in environments as diverse as those encountered in real driving situations, there are bound to be test samples which are quite dissimilar from any clear path training samples, yet are in fact image regions of clear path roadways.
There is a need for a clear path detection methodology which can continuously update and adapt its classifier based on recent clear path image regions which were correctly classified. Such a methodology can be used to improve the speed and accuracy of driving assistance systems.